adjust test tolerances for new isapprox behavior (#190)

Author: jrevels

test/HessianTest.jl

@@ -78,7 +78,7 @@ for f in DiffBase.VECTOR_TO_NUMBER_FUNCS
     g = ForwardDiff.gradient(f, X)
     h = ForwardDiff.hessian(f, X)
     # finite difference approximation error is really bad for Hessians...
-    @test_approx_eq_eps h Calculus.hessian(f, X) 0.01
+    @test isapprox(h, Calculus.hessian(f, X), atol=0.02)
     for c in CHUNK_SIZES
         println("  ...testing $f with chunk size = $c")
         cfg = ForwardDiff.HessianConfig{c}(X)

test/JacobianTest.jl

@@ -91,7 +91,7 @@ end
 for f in DiffBase.ARRAY_TO_ARRAY_FUNCS
     v = f(X)
     j = ForwardDiff.jacobian(f, X)
-    @test_approx_eq_eps j Calculus.jacobian(x -> vec(f(x)), X, :forward) FINITEDIFF_ERROR
+    @test isapprox(j, Calculus.jacobian(x -> vec(f(x)), X, :forward), atol=FINITEDIFF_ERROR)
     for c in CHUNK_SIZES
         cfg = JacobianConfig{c}(X)
 
@@ -114,7 +114,7 @@ for f! in DiffBase.INPLACE_ARRAY_TO_ARRAY_FUNCS
     v = zeros(Y)
     f!(v, X)
     j = ForwardDiff.jacobian(f!, zeros(Y), X)
-    @test_approx_eq_eps j Calculus.jacobian(x -> (y = zeros(Y); f!(y, x); vec(y)), X, :forward) FINITEDIFF_ERROR
+    @test isapprox(j, Calculus.jacobian(x -> (y = zeros(Y); f!(y, x); vec(y)), X, :forward), atol=FINITEDIFF_ERROR)
     for c in CHUNK_SIZES
         cfg = JacobianConfig{c}(X)
         ycfg = JacobianConfig{c}(zeros(Y), X)

test/utils.jl

@@ -10,4 +10,4 @@ const XLEN = CHUNK_THRESHOLD + 1
 const YLEN = div(CHUNK_THRESHOLD, 2) + 1
 const X, Y = rand(XLEN), rand(YLEN)
 const CHUNK_SIZES = (1, div(CHUNK_THRESHOLD, 3), div(CHUNK_THRESHOLD, 2), CHUNK_THRESHOLD, CHUNK_THRESHOLD + 1)
-const FINITEDIFF_ERROR = 1.5e-5
+const FINITEDIFF_ERROR = 3e-5